Exploring How Customers Interact With Advertising, Products, Brands, and Channels, using Multichannel Forensics.

February 09, 2010

Digital Profiles: Creating Each Profile

You have your data in a "spreadsheet", if you will, one row per customer, each column telling us something about that customer during the past year.Now, it is time to generate each Digital Profile.You are free to use whatever methodology you wish to use. I personally adore a methodology known as a "Factor Analysis", because the methodology is elegant, reducing the dimensionality of a complex dataset to a series of "factors".Here's what I do:

I calculate the mean and standard deviation of each variable, for later use.

I run a Factor Analysis.

I extract three or four "Factors".

I run a frequency distribution, to determine the median value for each Factor.

I've used Dummy Variables, I've used % of spend, and I've used $s spent. I've found that combinations of variables work best, from a practical standpoint, meaning that some variables are continuous, some are dummy variables.

Thanks. I think most literature says avoid mixing, but if it works and provides a meaningful interpretation - great!

One alternative might be to build a correlation matrix for variables that is "pieced together" using correlations suitable for binary x binary and binary x continuous etc. Then use a factor program like SAS Proc Factor that allows the input of a correlation matrix instead of raw data